With regard to algorithm for image enlargement processing, there are nearest neighbor method, bilinear method, bicubic method, and so on.
First, the nearest neighbor method inverse-transforms pixel coordinates of a transformation target into pixel coordinates of a transformation source, and lets the value of a pixel in the most vicinity be the pixel value of transformation target. Although transformation is simple, the method produces degraded image quality having a conspicuous jaggy etc.
Further, the bilinear method inverse-transforms pixel coordinates of a transformation target into pixel coordinates of a transformation source, and obtains the pixel value of transformation target by performing linear interpolation among 4 (=2×2) pixels in the vicinity. Although a jaggy is not conspicuous, the enlarged image gives an impression that it is a blurred. This is because the image is generated using a weighted average of 4 pixels in the vicinity.
Also, the bicubic method inverse-transforms pixel coordinates of the transformation target into pixel coordinates of transformation source, and performs interpolation by use of a cubic equation from 16 (=4×4) pixels in the vicinity. In comparison with the bilinear method, the bicubic method requires a large calculation amount, causing a low processing speed, although an image blur may be suppressed.
Further, with regard to an image enlargement processing technique, for example an “image processing apparatus and a control method therefor” is disclosed in the official gazette of the Japanese Laid-open Patent Publication No. 2008-33692. According to the above conventional example, in order to maintain the sharpness of an original image while restraining the occurrence of noise, first, a smoothed image data is generated in addition to an enlarged image data. Then, an emphasis coefficient is multiplied by a difference image data which is obtained by subtracting between the above two data. Thereafter, by adding the above multiplied result to the enlarged image data, the enlarged image is obtained. In short, the above technique is to perform unsharp mask processing upon the data after enlargement processing. For the image enlargement processing, the bicubic method is mainly used.
Further, as a proposal for image enlargement processing algorithm, for example, an “image processing apparatus” is disclosed in the official gazette of the Japanese Laid-open Patent Publication No. 06-38024. In this conventional example, in order to obtain an enlarged image in which the sharpness is preserved in an edge portion, a gradation change rate of an interpolated pixel is adjusted according to the degree of gradation change between adjacent pixels. Then, according to the above adjusted change rate, the gradation of the interpolated pixel is obtained. Typically, the following methods are exemplified: (1) to adjust the change rate from a gradation difference between adjacent pixels; (2) to adjust the change rate in consideration of the direction (positive or negative) of the gradation change, which is obtained from a gradation difference between adjacent pixels and also from a backward pixel; and (3) to adjust the change rate from a gradation difference between adjacent pixels after edge enhancement processing.